Stand-alone artificial intelligence - The future of breast cancer screening?

Stand-alone artificial intelligence - The future of breast cancer screening?

by Ioannis Sechopoulos, Ritse M. Mann 

The Breast: FULL LENGTH ARTICLE| VOLUME 49, P254-260, FEBRUARY 01, 2020

Although computers have had a role in interpretation of mammograms for at least two decades, their impact on performance has not lived up to expectations. However, in the last five years, the field of medical image analysis has undergone a revolution due to the introduction of deep learning convolutional neural networks – a form of artificial intelligence (AI). Because of their considerably higher performance compared to conventional computer aided detection methods, these AI algorithms have resulted in renewed interest in their potential for interpreting breast images in stand-alone mode.

Artificial intelligence in digital breast pathology: Techniques and applications

Artificial intelligence in digital breast pathology: Techniques and applications

by Asmaa Ibrahim, Paul Gamble, Ronnachai Jaroensri, Mohammed M. Abdelsamea, Craig H. Mermel, Po-Hsuan Cameron Chen, Emad A. Rakha

The Breast: ORIGINAL ARTICLE| VOLUME 49, P267-273, FEBRUARY 01, 2020

Breast cancer is the most common cancer and second leading cause of cancer-related death worldwide. The mainstay of breast cancer workup is histopathological diagnosis - which guides therapy and prognosis. However, emerging knowledge about the complex nature of cancer and the availability of tailored therapies have exposed opportunities for improvements in diagnostic precision. In parallel, advances in artificial intelligence (AI) along with the growing digitization of pathology slides for the primary diagnosis are a promising approach to meet the demand for more accurate detection, classification and prediction of behaviour of breast tumours.

Winter is over: The use of Artificial Intelligence to individualise radiation therapy for breast cancer

Winter is over: The use of Artificial Intelligence to individualise radiation therapy for breast cancer

by Philip M.P. Poortmans, Silvia Takanen, Gustavo Nader Marta, Icro Meattini, Orit Kaidar-Person 

The Breast: FULL LENGTH ARTICLE| VOLUME 49, P194-200, FEBRUARY 01, 2020

Artificial intelligence demonstrated its value for automated contouring of organs at risk and target volumes as well as for auto-planning of radiation dose distributions in terms of saving time, increasing consistency, and improving dose-volumes parameters. Future developments include incorporating dose/outcome data to optimise dose distributions with optimal coverage of the high-risk areas, while at the same time limiting doses to low-risk areas. An infinite gradient of volumes and doses to deliver spatially-adjusted radiation can be generated, allowing to avoid unnecessary radiation to organs at risk.